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We consider scenarios where we have zero instances of real pedestrian data (e.g., a newly installed surveillance system in a novel location in which no labeled real data or unsupervised real data exists yet) and a pedestrian detector must be developed prior to any observations of pedestrians. Given a single image and auxiliary scene information in the form of camera parameters and geometric layout...

Detailed and accurate characteristics of preimplantation embryos are fundamental for a deep understanding of their development. Recent studies indicate that various geometric features of cells, such as size, shape, volume, and position play a significant role in embryo growth. However, a quantitative assessment of these characteristics first needs a segmentation of the individual cells. The manual...

This paper describes the development of the IAS-Society and the trends in the Intelligent Autonomous Systems conferences. The first IAS conference was held in 1986 and was the first conference on this topic. The Society, founded in 1994, laid the basis for the organization of the IAS conferences. The topics presented at the successive IAS conferences showed clearly the development of the field of...

To enable real-time, person-independent 3D registration from 2D video, we developed a 3D cascade regression approach in which facial landmarks remain invariant across pose over a range of approximately 60°. From a single 2D image of a person's face, a dense 3D shape is registered in real time for each frame. The algorithm utilizes a fast cascade regression framework trained on high-resolution 3D face-scans...

The parameters estimated by Structure from Motion (SFM) contain inherent indeterminacies which we call gauge freedoms. Under a perspective camera, shape and motion parameters are only recovered up to an unknown similarity transformation. In this paper we investigate how covariance-based uncertainty can be represented under these gauge freedoms. Past work on uncertainty modeling has implicitly imposed...

Pose Machines provide a sequential prediction framework for learning rich implicit spatial models. In this work we show a systematic design for how convolutional networks can be incorporated into the pose machine framework for learning image features and image-dependent spatial models for the task of pose estimation. The contribution of this paper is to implicitly model long-range dependencies between...

Correlation is a very effective way to align intensity images. We extend the correlation technique to point set registration using a method we call kernel correlation. Kernel correlation is an affinity measure, and it is also a function of the point set entropy. We define the point set registration problem as finding the maximum kernel correlation configuration of the the two point sets to be registered...

The Precision Freehand Sculptor (PFS) is a compact, handheld, intelligent tool to assist the surgeon in accurately cutting bone. A retractable rotary blade on the PFS allows a computer to control what bone is removed. Accuracy is ensured even though the surgeon uses the tool freehand. The computer extends or retracts the blade based on data from an optical tracking camera. Three users used each of...

Here we model the effect of non-overlapping voxels on image registration, and show that a major defect of overlap-only models—their limited capture range—can be alleviated. Theoretically, we introduce a maximum likelihood model that combines histograms of overlapping and non-overlapping voxels into a common joint distribution. The convex problem for the joint distribution is solved via iterative application...

In this paper we present an algorithm to correct 3D reconstruction errors of 3D ultrasound catheter caused by ultrasound image thickness. We also provide a method to quickly measure ultrasound image plane’s thickness. With thickness correction registration accuracy of navigation system using 3D ultrasound catheters can be improved by 20%.

In this session the three participants presented a short overview of what they believe to be key issues and milestones that have brought us to the present. They then give their perspective as to the major issues for the future. Personally, I feel the major lesson from the past is that the notion of general purpose robotic devices proved to be too ambitious, and flawed as a generating principle. Instead,...

We present a novel approach to image segmentation using iterated Graph Cuts based on multi-scale smoothing. We compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the previous process, and set the probability as the t-link of the graph for the next process. The proposed method can segment the regions...

The visual medium evolved from early paintings to the realistic paintings of the classical era to photographs. The medium of moving imagery started with motion pictures. Television and video recording advanced it to show action “live” or capture and playback later. In all of the above media, the view of the scene is determined at the transcription time, independent of the viewer. We have been...

To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model this process using hierarchical Markov random field (HMRF), and suggest a broader view that clique potentials in MRF models can be used to encode any local decision rules. A topology-dependent multiscale hierarchy is used to...

Fat and muscle layers in the human soft-tissue causes degradation of resolution and distortions of shape in ultrasound images of organs. Novel ultrasonic applications such as registration between CT and ultrasound images, requiring comparable levels of accuracies between modalities could suffer from the distortions in ultrasound images. In this work, we describe a possible method to compensate or...

We present a novel approach to segmenting video using iterated graph cuts based on spatio-temporal volumes. We use the mean shift clustering algorithm to build the spatio-temporal volumes with different bandwidths from the input video. We compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the previous...

In this paper, we present a robust face alignment system that is capable of dealing with exaggerating expressions, large occlusions, and a wide variety of image noises. The robustness comes from our shape regularization model, which incorporates constrained nonlinear shape prior, geometric transformation, and likelihood of multiple candidate landmarks in a three-layered generative model. The inference...

Shape-based registration is a process for estimating the transformation between two shape representations of an object. It is used in many image-guided surgical systems to establish a transformation between pre- and intra-operative coordinate systems. This paper describes several tools which are useful for improving the accuracy resulting from shape-based registration: constraint analysis, constraint...

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